Reflections on a “systems approach” for Drylands CRP-Brian Keating

Reflections on a “systems approach” for Drylands CRP

Brian Keating and ISAC colleagues

“…in spite of fashionable lip-service to systems ideas, and in spite of frequent exhortations to use a systems approach, we are rarely told what it consists of, or exactly how we might use it.

There has been a notable lack of determined persistent efforts, first to define what ‘a systems approach’ means and then to go out and use it in tackling problems,

in order to experience that interaction between theory and practice which is the best recipe for intellectual progress.”

Peter Checkland (1981) Systems Thinking, Systems Practice.

This topic has a long and deep literature ....(often outside of agriculture)

Models and on-farm participative research

• Agriculture is part of a “human activity system” with production and management elements

• Agriculture is only part of a systems approach to food and nutritional security ad poverty reduction

• Our systems approach should be focused on “problem solving” at the science-practice interface

• Innovation in agri-food systems needs more than research.

Four observationsSelf-evident

Systems focus

Farm System

Various External

Environments

OUTPUTS

CropsSoil

Animals

INPUTS

CLIMATE

PRODUCTION SYSTEM

MARKETS

MANAGEMENT SYSTEM

Monitoring

Deliberative planning & control

Action

Internal EnvironmentNeeds, values, goals, etc Knowledge, cognitive limits, etc.Resources

SURFACE AND GROUND WATER

Adapted from Sorensen & Kristensen, 1992

Policyenvironment

Hierarchy of scales and multiple drivers of change

Herrero et al, Science (2010)



• Agriculture is only part of a systems approach to food and nutritional security and poverty reduction



Four observations

AGRICULTURE - Sustainable Productivity Improvement

Innovation research & extension

InfrastructureFinance &

Responsible Investment

Human Resources

Markets & Trade

Resource Tenure

Enabling Policies, Regulations & Institutions

Supporting Private Sector and Civil Society Engagement and Investment

International Leadership & Coordination Global Public GoodsDomestic Policy Reform

Understanding Risks and Opportunities – Foresight and Scenario Analysis

Transforming Small Scale Agriculture / Agribusiness

Food & Nutrition Security(availability, access, utilization, stability)

Inclusive Growth & Jobs for rural women, men and youth

Growth, Jobs and Resilience

Agriculture and Food Sector Growth and Efficiency

Food Availability

& UtilisationFood Affordability

Food Availability

Nutrition Interventions

Food Utilisation

Human ProductivitySecurity and stability

Food Affordability

Social Protection

Food Affordability


• Agriculture is part of a “human activity system” with production and management elements and a wider context


• Our systems approach should be focused on “problem solving” at the science-practice interface (Impact focused)


Four opening observations

Systems thinking - systems practice

– Creation of knowledge relevant to system design and management

• --- but there has always been the problem of “adoption”.

– Use of scientific knowledge in intervention in system owners’ design and management

• This is the essence of “systems PRACTICE”.

• Embedded in a strong “problem solving” paradigm

Peter Checkland (1981) .

increasing ‘integration’

Jackson (2000) Systems Approaches to Management

The Systems Movement

Systems thinking in the disciplines Study of systems in

their own right

Systems thinking for “problem solving”

(Multidisciplinary)

(in practice)

organisational integration

interactive science -practice integration

Systems thinking is integrative (cf. analytical thinking)





• Innovation in agri-food systems needs more than just research.

Four opening observations

What is an Innovation System?

= The conditions that are needed to enable innovation. Definition: A network of organizations, enterprises, and individuals focused on bringing new products, new processes, and new forms of organization into economic and social use, together with the practices or institutions and policies that affect their behavior and performance.

A dynamic view of “Innovation systems”

Adapted from A. Hall (2012) Partnerships in agricultural innovation - Who puts them together and are they enough? In OECD Conference on Improving Agricultural Knowledge and Innovation systems

Technology triggers

Market triggers

Social triggers

Environmental triggers

Research Organisations

Enterprises

Support Organisations

Markets and Consumers

“Go-between” Organisations

Protocols

Enabling Policy Environment

Innovations of

economic, environmental or social significance

New capacity to innovate

Long history of systems research methods

A Research Typology(Oquist, 1978)

Acta Sociologica l21, 143-163.

• Descriptive research– e.g. broaden the knowledge of the production and

management system, characterise system resources

• Predictive (nomothetic) research– e.g., Test understanding by developing predictive and

generalisable models of a system

• Prescriptive (policy / operations) research– e.g., Use data or models to identify optimal strategies for

desired outcome

• Participatory action research– e.g., learn via inquiry within the life experience of

participantsEach type assumes and builds on the prior type

How the world works!

How to change the

world !

In Drylands we are going to need all four types of research – in the journey from Discovery through Diagnosis to Pilot and Scale Out.

This journey will not necessarily be linear

Methodological innovation – FSR foundation

From Dillon and Anderson (1984), after Collinson (1982)

Linking Operations Research to FSR

In the late 80’s and early 90’s, McCown and colleagues combined the “simulation modelling of agricultural systems with the client-orientation of FSR”

Action Learning

IntentLearningAction

Knowledge When the main intent is deliberative “changing of a reality” (action), the learning is action learning.

Plan

ActReflect

Observe

Action Learning

Cycle

An elaborated view of Farming Systems Research (FSR)

A Framework for intervention that substitutes a production systems model for the actual system in facilitated action learning (after McCown, 2008)


• On-farm ==> Relevance

• Participative ==> Ownership and relevance

• Systems Analysis (incl. Models)==> Explanation and generality

• Generality– Extrapolation in time (over

variable seasons)– Extrapolation in space (other soils,

climates, livelihood circumstances)


A crowded history of research for development approaches

1980’s

1990’s

2000’s

1960’s

1970’s

On Station Research

Extension based technology transfer

NIE

FSROFR

RRA

PRAPAR

PTDFTR

FFS

PPB

AKIS

PI&D

IRD

BB’sMBTs

SRLsFARMSCAPE

INRMIGNRM

IAR4DIS

IP

ERI

CASE

PLAR

RDs

CCNR

AR

ARD

FS

What trends can we observe ?

• Moving from descriptive to predictive/diagnostic approaches including the use of systems analysis and modelling tools

• Increasing participation from a broader range of actors

• Emergence of a value chain focus to complement an on-farm focus

• Increasing recognition of the significance of enabling institutions and governance

• Contested paradigms; hard systems vs soft systems; positivism vs constructivism; researcher knowledge / farmer knowledge

• Greater recognition of social equity and gender issues

Some propositions for Drylands to consider in shaping a “systems

approach”

1. A systems approach shaped by problem solving “in practice”

• A “systems approach” that is best defined in terms of the outcomes we seek.

• That is, it is a “whatever it takes” approach to improving food security, reducing poverty and enhancing resilience in the world’s drylands.

• Our approach does not prejudge the need for a particular technology, a particular commodity-related intervention or a particularly disciplinary consideration.

• Approach draws upon diverse sources of scientific and local knowledge to improve the food security and livelihoods of the dryland peoples.

Systems research at the scale of impact

2. Agricultural Livelihood System

• The primary focus for our systems approach (level n) will be the “agricultural livelihood system”.

• That is the set of farm, farming and human activity systems that determine the livelihood opportunities for agricultural households, enterprises or communities.

• Implicit in this focus is consideration of the food and

nutritional security, health and well being, employment and income generation of dryland peoples.

3. Systems Context

• Our systems context (n+1) is the wider environmental and institutional setting

• Including government policy, business activity, input and output markets, value chains, knowledge systems, social and cultural norms, gender bias etc.

• We consider this wider context to be the “innovation system” and we recognise scientific research is only one part of the innovation process, albeit a potentially catalytic or transformational part

4. Science based diagnosis and intervention design

• Our explanatory insight (n-1) comes from our descriptive and predictive capacity around the key components and the many interactions that shape agricultural livelihoods.

• Components include but are not limited to crop, livestock and tree options and technologies within farming systems, agricultural inputs and output availability and prices, natural resources used in farming in particular soil fertility and water management, tillage systems, energy systems, labour and capital, nutrition and health consequences of diets, education systems and off-farm income generation …..

• We can’t discard our scientific method/value-add in our efforts to get more participative and relevant

5. An evolving research methodology

• Diagnosis of constraints and opportunities at the agricultural livelihood level will be our primary entry point for “discovery” science in dryland systems.

• These will be holistically analysed for development constraints in order to identify the system bottlenecks and effective remedies.

• For the latter we will draw upon indigenous knowledge as well as technological discoveries and developments from other CRPs and the wider agricultural R&D system.

6. “Fit for purpose” participative approaches

• Efforts to simulate desired change supported by appropriate engagement/innovation brokering at appropriate scales with appropriate actors (eg. farmers, community groups, value chain and market participants, private sector investors, government policy etc.)

- Not a one size fits all …

• Research contribution will be always informed by a solid scientific base, including efforts to interpret system functionality and generalize interventions to other times and places

• National and regional institutions and development partners will be drawn in at the outset and the “scale out” objective adaptively planned as a “research in development” activity

7. Cross-cutting research methods and capabilities are needed

• Spatial information systems

• Data acquisition and management (includes household survey methods and human research ethics)

• Farming systems modelling (development, validation, deployment in diagnosis and participative design )

• Bio-economic modeling / agent based socio-ecological modeling (Households/communities)

• Value chain and business systems analysis

• Building gender considerations into research for/in development

• Global and regional change scenarios (links to CCAFS ?)

• Capacity building in participative process/ knowledge brokering – Innovation Platforms, Hubs, Facilities, PPPs etc

Get serious with SRT 1 and 4

Thankyou

Modelling and systems analysis tools

Integrated Modelling MethodologySystems

characterisation

soil

ANIMAL

crops

TPS

herd

livestock

Biological simulationsystem

Databases

limitsconstraintsresourcesmgmt practices

Multiple criteriaLP models

DYNAFEED

Sustainableresourcemanagementstrategies

Socio-economic

I/O

Herrero et al. 1996, 1997

NUANCES-FARMSIM

Van Wijk et al., 2009, Ag. Systems

Integrated analysis tool (IAT)

Crop, forage yield

Feasible/most profitable strategy

LivestockModel

EconomicModel

Inputs

Climate

Soil Management

Prices

Costs

Labour

Machinery

Outputs

Crops

Forage

Cattle

Labour

IncomeAPSIM

Crop-ForageModel

Herd structure & Management

Livestockyield

Forageyield

Household Modelling Workshop Dockside 19th-20th November 2013 Slide 13

Modelling alternative household resource allocations Baseline

household surveyN>500

APSFarm-LivSimRelevant interventions

Better informed discussions, investments & decisions

Profits Risks SustainabilityFood security

SIMLESA program http://simlesa.cimmyt.org/

•Stubble management•N fertilisation

Courtesy of D. Rodriguez

http://simlesa.cimmyt.org/

• Longitudinal data• Participatory methods• Key informants

• Systems’ classification

• Selection of farms

• Household modeling• Sensitivity analyses

• Participatory appraisals• Recommendation domains• Toolboxes of interventions• Farmers / NARS

• Stakeholder workshops• Participatory appraisals

Participatory modelling

Ecoregion

Farms

CBA

Case studies

Range of interventions to test

for each system (filtering)

Scenario formulation(Farm and policy

level)

Selection of a fewer range of

options

Site targeting

Dissemination &

implementation

Policy-making

Testing options in the field

(Herrero, 1999)

Baseline data

Data collection protocol :

– Climate– Family structure– Land management– Livestock

management– Labour allocation– Family’s dietary

pattern– Farm’s sales and

expenses

Systems modelling approachesClass of model An example of model application Model Examples Gene to Phenotype

- more efficient crop improvement programs

QTL based models (e.g.Yin et al., 2004)

Crop-Soil - identification of optimal agronomic practices and/or varietal adaptation

Simulation Models (CERES, GRO models)

Farming System - farming systems design within soil, climate and management constraints

Systems Simulation models (e.g., APSIM, DSSAT, CROPSYS)

Farm Household / Enterprise

- optimal resource allocation (inputs, labour, enterprise mix) to raise farm productivity

Bio-economic optimisation models (e.g. MIDAS, MUDAS); NUANCES

Regional Dynamics

- cross-sectoral responses to change drivers and intervention strategies

CGE Models, Regional Stocks and Flows, Agent-based models

National Economy

- impacts of interventions in the agricultural sector on economic growth, employment, balance of trade etc

National CGE models (e.g. MONASH) or stocks and flows models (e.g. ASFF)

Earth Systems/ Global Economy and Trade

- climate change impacts on global food supply and agricultural trade

Global Trade models (e.g. GTAP, IMPACT, IFPRI models)

Global Scenarios

Regional Scenarios

Farmer/village perspectives

Action research

Participatory scenario building

Global visioning activities

Global impacts modelling

Regional impacts

modelling

Household & community

impacts modelling

Linking research at different levels

Thornton et al 2012

A more integrative approach in the CGIAR ?

From Stripe Review – NRM Research in CGIARhttp://www.sciencecouncil.cgiar.org/fileadmin/templates/ispc/HOME/NRM_StripeReport_Proof4_WEB.pdf

Natural Resource Management

(incl. agronomy)

Genetic and other

technologies

Enabling Institutions

DevelopmentImpact